Atcold/NYU-DLSP21
NYU Deep Learning Spring 2021
Comprehensive course materials covering foundational deep learning topics (backpropagation, gradient descent, CNNs, RNNs) with a novel emphasis on latent variable energy-based models as a core framework. Includes lecture slides, Jupyter notebooks, and video transcriptions organized into three modules, each with accompanying practicum assignments. Built progressively to enable advanced applications in the second half of the semester by establishing EBMs as a foundational concept rather than an advanced topic.
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Nov 11, 2025
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